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Apply for an Embedding Key

Currently, WiseMind AI requires users to configure their own Embedding Keys. The following models are supported:

All costs generated by using the key are charged entirely by the respective model provider and have no relation to WiseMind AI.

Model ProviderApplication URLModel ListDefault Value
Tencent HunyuanGet API KeyGet Model Listhunyuan.tencentcloudapi.com
MiniMax AIGet API KeyGet Model Listembo-01
Zhipu AIGet API KeyGet Model Listembedding-2
Baidu QianfanGet API KeyGet Model Listembedding-v1
Alibaba TongyiGet API KeyGet Model Listtext-embedding-v1
OpenAIGet API KeyOfficial Websitetext-embedding-3-small
OpenRouterGet API KeyOfficial Websiteopenai/text-embedding-3-small
GeminiGet API KeyOfficial Websitegemini-embedding-001
CloudflareGet API TokenModel List@cf/baai/bge-m3
Voyage AIGet API KeyOfficial Websitevoyage-3.5
CohereGet API KeyOfficial Websiteembed-v4.0
Jina AIGet API KeyModel Listjina-embeddings-v4

Configure and test

Open Settings → Model Settings → Embedding Models in WiseMindAI. Select a provider, then enter the API key, model name, and endpoint. Cloudflare also requires an Account ID.

After saving, select Test on the current model card. A successful test displays the vector dimensions, confirming that the model can convert text into vectors. The test does not change your active model or create a production document index.

Cost notice

Both online tests and document analysis call the provider's service and may incur a small fee. Pricing and quotas are determined by the provider.

Recommendations

  • For primarily Chinese content, choose an Embedding model that explicitly supports Chinese or multiple languages.
  • If you change the Embedding model for an existing knowledge base, reprocess its documents to avoid mixing vectors from different models.
  • If the test succeeds but document chat still cannot find content, make sure the document analysis has completed.
  • Models differ in dimensions, price, and maximum input length. Compare a small set of documents before choosing a model for a long-term knowledge base.